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A probabilistic methodology is proposed in this paper to estimate the equivalent initial flaw size (EIFS) distribution accounting for various sources of variability, uncertainty and error, for mechanical components with complicated geometry and multi-axial variable amplitude loading conditions.
This study presents a qualitative perspective to identifying and understanding these trade-offs and probing the various sources of variability in high-κ RRAM.
Because nested designs are often employed with the objective of estimating various sources of variability, all the factors are usually chosen as random.
The metrics that ensue from this model are recommended to be reported along with the percent test-retest metric as they capture various sources of variability in the PET test-retest experiments in a succinct way.
A report by the National Academy of Sciences National Research Councill, 2014) raised an issue regarding the contribution of various sources of variability to the data used to construct ROC curves.
The metrics that ensue from this model such as ICC, RC and WSVC are recommended to be reported along with the percent test-retest metric as they capture various sources of variability in the PET test-retest experiments in a succinct way.
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In our model, we create a unified treatment of the various sources of kinematic variability (sensorimotor noise, external perturbations, systematic load or force fields etc).
Equations describing compounds kinetics in Simcyp are published and various sources of interindividual variability of principal parameters are previously discussed.
Although there exist various sources of interindividual variability, in this study we focused on the predictable impact of variations in anatomical and physiological parameters linked to covariates.
Finally, we want to acknowledge that the mechanistic deterministic modelling approach we employed here, while appealing because of its built-in tractability, is limited in the sense that everything is assumed as an average at a patient population/hospital level, with no explicit account for various sources of heterogeneity, variability and uncertainty.
QTL analyses are sensitive to various sources of variability not just variability that is due to genotypic variation.
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